Predictive Trade Promotion Planning

Case Study: Predictive Trade Promotion Planning

Operating in a highly competitive market, this leading food company’s success relies heavily on effectively planning and executing promotional and trade investment activities. Unfortunately, the existing sales and marketing planning capabilities did not meet their needs for winning in the market. Activities in the field were being planned and tracked through multiple tools, data was collected manually, more time was spent on data entry than analytics, and insights were inconsistently shared. As their trade investment levels rose steadily, our client needed to improve the accuracy of their sales forecasting and manage their sales resources more efficiently.

Challenges & Solutions

Challenge 1: Trade promotion planning activities were inconsistent and difficult to integrate.Solution: Clarkston helped improve our client’s end-to-end collaborative trade planning process and implemented Oracle’s Demantra Predictive Trade Planning software. Beginning by designing and hosting the solution in a ‘Clarkston Design Lab,’ Clarkston enabled our client to experience a prototype in a hands-on environment prior to system development. The solution also utilized a SaaS Demand Signal Repository (DSR) to harmonize and cleanse demand data originating from disparate sources to feed the new trade system. The DSR enabled our client to take advantage of an integrated collection of demand data to conduct more robust analytics and better predict their demand curve.

Challenge 2: Calculating trade promotion ROI was cumbersome.Solution: Like most companies in the Consumer Products industry, our client performed manual ROI analysis on promotional events and, in some cases, no analysis at all. The new solution automated post-event analysis to give an up-to-date account of all past events. Additionally, predictive analytics capabilities provided our client a statistically generated estimate on future returns on promotional investments based upon different promotional mix scenarios. Therefore, our client was able to make optimal investment decisions to best reach their goals.